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【正文】 ed times. 21 Evaluating the Model 1. How does the model describe the relationship among variables? 2. Closeness of ‘ Best Fit’ 3. Assumptions met 4. Significance of estimates 5. Correlation among variables 6. Outliers (unusual observations) 22 Testing Overall Significance 1. Test whether there is linear relationship between Y and all the independent variables. 2. 2. Use F statistic. 3. Hypothesis 4. H0: ? 1 = ? 2 = ... = ? P = 0 There is no linear relationship between Y and independent variables. H1: At least there is a coefficient isn’ t equal to 0. At least there is an independent variable influences Y 23 Testing Overall Significance Computer Output Analysis of Variance Sum of Mean Source DF Squares Square F Value ProbF Model 2 Error 3 C Total 5 P n P 1 n 1 MSR / MSE p Value 24 Transformations in Regression Models ?Nonlinear models that can be transformed into linear models (convenient to carry out OLS). ?Data Transformation ?Multiplicative Model Example Y X X Y X X i i i i i i i i ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 0 1 2 0 1 1 2 2 1 2 ln ln ln ln ln 25 SquareRoot Transformation Y X X i i i i ? ? ? ? ? ? ? ? 0 1 1 2 2 ?1 0 ?1 0 Y X 1 26 Logarithmic Transformation Y X X i i i i ? ? ? ? ? ? ? ? 0 1 1 2 2 ln ln ?1 0 ?1 0 Y X 1 27 Exponential Transformation Y i i e X X i i ? ? ? ? ? ? ? 0 1 1 2 2 ?1 0 ?1 0 Y X 1 28 演講完畢，謝謝觀看！
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